Fault diagnosis method based on supervised incremental local tangent space alignment and SVM

Applied Mechanics and Materials

Volumn 34-35, Issue , 2010, Pages 1233-1237

  Wang, Guangbin ^a,b   Zhao, Xianqiong ^b   He, Yuhui ^b  

^a HUNAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b CENTRAL SOUTH UNIVERSITY   (China)

Author keywords

Fault diagnosis; Supervised incremental LTSA; SVM

Indexed keywords

FAULT DIAGNOSIS; FAULT DIAGNOSIS METHOD; FAULT SIGNAL; FUALT DIAGNOSIS; LOCAL TANGENT SPACE ALIGNMENT; NON-LINEAR; ROLLER BEARING FAULT; SUPERVISED INCREMENTAL LTSA; SVM;

ALIGNMENT; DATA HANDLING; FEATURE EXTRACTION; GEARS; MANUFACTURE; MECHANICAL ENGINEERING; ROLLER BEARINGS; VECTOR SPACES;

SUPPORT VECTOR MACHINES;

EID: 78650903150     PISSN: 16609336     EISSN: 16627482     Source Type: Book Series    
DOI: 10.4028/www.scientific.net/AMM.34-35.1233     Document Type: Conference Paper

References (10)

1. H.S. Seung and D.L. Daniel. Science. 290(2000), p.2268-2269.
2. S. Roweis and L. Saul. Science. 290(2000), p.2323-2326.
3. M.Belkin and P.Niyogi. Neural Computation. 15(2003), p.1373-1396.
4. Zhang Zhenyue and Zha Hongyuan. SIAM Journal on Scientific Computing.26(2005), p.313-338.
5. M.H.Law and A.K.Jain. Pattern Analysis and Machine Intelligence, IEEE Transcations on, 28(2006), p.377-391.
6. O.Kouropteva, O.Okun and N. IPietik. Pattern recognition. 38(2005), p.1764-1767.
7. Xiaoming Liu, Jianwei Yin and Zhilin Feng, etl. Artificial Neural Networks in Pattern Recognition, Ulm, Germany, 2006:107-121.
8. D.Ridder, O.Kouropreva and O.Okun. Proceedings of Artifical Neural Networks and Neural Information Processing, 2003, LNCS2714, Springer, 333-341.
9. L.Saul and S. Roweis. Journal of Machine Learning Research, 4(2002), p.119-155.
10. Information on http://www.eecs.case.edu/laboratory/bearing.